Regression modelEconometrics / time series

Nonlinear SARIMA Model

The Nonlinear SARIMA model extends the classical Seasonal ARIMA framework by replacing the linear conditional mean function with a nonlinear specification — such as threshold switching or smooth transition — while retaining seasonal differencing and lag structure. It is used when seasonal time series exhibit regime-dependent dynamics, asymmetric adjustment, or other nonlinear patterns that a linear model cannot capture.

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Sources

  1. Tong, H. (1990). Non-linear Time Series: A Dynamical System Approach. Oxford University Press. ISBN: 978-0198523000
  2. Franses, P. H., & van Dijk, D. (2000). Non-linear Time Series Models in Empirical Finance. Cambridge University Press. ISBN: 978-0521779654

Related methods

ScholarGateNonlinear SARIMA Model (Nonlinear Seasonal Autoregressive Integrated Moving Average Model). Retrieved 2026-06-04 from https://scholargate.app/tr/econometrics/nonlinear-sarima-model